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arXiv 1604.04895cs.CY
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尺度指标与规划平面:探索城市形态、能源效率与碳排放关系的指标与可视化工具

Scaling indicator and planning plane: an indicator and a visual tool for exploring the relationship between urban form, energy efficiency and carbon emissions

Fouad Khan, Laszlo Pinter

摘要:

生态系统和其他自然恢复系统在其要素的大小分布中表现出异速生长比例。在本文中,我们定义了一个异速生长启发的城市尺度指标,这是量化复杂系统的层次结构组成的弹性承担的第一步。尺度指标是使用大型人口普查数据集计算的,类似于空间分析中的分形维数。缺乏数值的严谨性和由此导致的缩放指标的变化-在使用盒子计数机制计算城市分形维数时所固有的-一直是采用分形维数作为城市指标的障碍之一。这里开发的城市内人口密度分布缩放指标是使用产生可复制结果的方法计算的,使用2010年美国人口普查2010年和2007年美国经济普查的大型人口普查数据集。我们发现,日益扩大的差距--用大都市统计区人口普查区块人口密度分布的拟议指标(使用美国2010年人口普查数据)来衡量--对城市的能源消耗效率和碳排放产生了不利影响,并导致城市碳足迹增加。然后,我们将规划平面定义为将缩放指标分析纳入政策和决策的可视化和分析工具。

英文摘要:

Ecosystems and other naturally resilient systems exhibit allometric scaling in the distribution of sizes of their elements. In this paper we define an allometry inspired scaling indicator for cities that is a first step towards quantifying the resilience borne of a complex systems' hierarchical structural composition. The scaling indicator is calculated using large census datasets and is analogous to fractal dimension in spatial analysis. Lack of numerical rigor and the resulting variation in scaling indicators -inherent in the use of box counting mechanism for fractal dimension calculation for cities- has been one of the hindrances in the adoption of fractal dimension as an urban indicator of note. The intra-urban indicator of scaling in population density distribution developed here is calculated for 58 US cities using a methodology that produces replicable results, employing large census-block wise population datasets from the 2010 US Census 2010 and the 2007 US Economic Census. We show that rising disparity -as measured by the proposed indicator of population density distribution in census blocks in metropolitan statistical areas (using US Census 2010 data) adversely affects energy consumption efficiency and carbon emissions in cities and leads to a higher urban carbon footprint. We then define a planning plane as a visual and analytic tool for incorporation of scaling indicator analysis into policy and decision-making.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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